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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        About MultiQC

        This report was generated using MultiQC, version 1.30

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2025-10-28, 12:57 MDT based on data in: /nfs/home/rsbg/01_fastq/04_emily_ebel_bulk_midgut_data_eg_RNAseq/HunterPipeline/02_Hisat2/logs

        General Statistics

        Showing 18/18 rows.
        Sample Name% Aligned
        22_WNV_A_S1
        44.4%
        22_WNV_B_S2
        46.6%
        22_WNV_C_S3
        36.9%
        22_mock_A_S4
        71.5%
        22_mock_B_S5
        41.0%
        22_mock_C_S6
        14.3%
        26_WNV_A_S7
        15.4%
        26_WNV_B_S8
        13.4%
        26_WNV_C_S9
        17.6%
        26_mock_A_S10
        44.7%
        26_mock_B_S11
        41.4%
        26_mock_C_S12
        17.3%
        30_WNV_A_S13
        62.5%
        30_WNV_B_S14
        54.4%
        30_WNV_C_S15
        57.5%
        30_mock_A_S16
        46.7%
        30_mock_B_S17
        70.1%
        30_mock_C_S18
        68.1%

        Bowtie 2 / HiSAT2

        Results from both Bowtie 2 and HISAT2, tools for aligning reads against a reference genome.URL: http://bowtie-bio.sourceforge.net/bowtie2; https://ccb.jhu.edu/software/hisat2DOI: 10.1038/nmeth.1923; 10.1038/nmeth.3317; 10.1038/s41587-019-0201-4

        Paired-end alignments

        This plot shows the number of reads aligning to the reference in different ways.

        Please note that single mate alignment counts are halved to tally with pair counts properly.

        There are 6 possible types of alignment:

        • PE mapped uniquely: Pair has only one occurence in the reference genome.
        • PE mapped discordantly uniquely: Pair has only one occurence but not in proper pair.
        • PE one mate mapped uniquely: One read of a pair has one occurence.
        • PE multimapped: Pair has multiple occurence.
        • PE one mate multimapped: One read of a pair has multiple occurence.
        • PE neither mate aligned: Pair has no occurence.
        Created with MultiQC